How do we find Census tracts that intersect with the Los Angeles metro area?
Find all Census tracts in CA.
library(tigris)library(tidyverse)library(sf)options(tigris_use_cache =TRUE)# CRS used: NAD27 / California zone VIIca_tracts <-tracts(state ="CA", cb =TRUE) %>%st_transform(4267) %>%print()
Simple feature collection with 9109 features and 13 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: -124.4085 ymin: 32.53438 xmax: -114.1304 ymax: 42.00966
Geodetic CRS: NAD27
First 10 features:
STATEFP COUNTYFP TRACTCE AFFGEOID GEOID NAME
1 06 037 294610 1400000US06037294610 06037294610 2946.10
2 06 059 011402 1400000US06059011402 06059011402 114.02
3 06 019 001304 1400000US06019001304 06019001304 13.04
4 06 037 273700 1400000US06037273700 06037273700 2737
5 06 037 207501 1400000US06037207501 06037207501 2075.01
6 06 053 010900 1400000US06053010900 06053010900 109
7 06 059 087403 1400000US06059087403 06059087403 874.03
8 06 037 242100 1400000US06037242100 06037242100 2421
9 06 037 408134 1400000US06037408134 06037408134 4081.34
10 06 001 451704 1400000US06001451704 06001451704 4517.04
NAMELSAD STUSPS NAMELSADCO STATE_NAME LSAD ALAND
1 Census Tract 2946.10 CA Los Angeles County California CT 823808
2 Census Tract 114.02 CA Orange County California CT 1136419
3 Census Tract 13.04 CA Fresno County California CT 1307803
4 Census Tract 2737 CA Los Angeles County California CT 690352
5 Census Tract 2075.01 CA Los Angeles County California CT 134327
6 Census Tract 109 CA Monterey County California CT 3736271
7 Census Tract 874.03 CA Orange County California CT 630332
8 Census Tract 2421 CA Los Angeles County California CT 459615
9 Census Tract 4081.34 CA Los Angeles County California CT 884018
10 Census Tract 4517.04 CA Alameda County California CT 2005363
AWATER geometry
1 0 MULTIPOLYGON (((-118.2624 3...
2 0 MULTIPOLYGON (((-117.9128 3...
3 0 MULTIPOLYGON (((-119.7537 3...
4 0 MULTIPOLYGON (((-118.4583 3...
5 0 MULTIPOLYGON (((-118.255 34...
6 15260 MULTIPOLYGON (((-121.3902 3...
7 0 MULTIPOLYGON (((-117.9145 3...
8 0 MULTIPOLYGON (((-118.2358 3...
9 0 MULTIPOLYGON (((-117.9037 3...
10 0 MULTIPOLYGON (((-121.7975 3...
Find Los Angeles CBSA.
la_metro <-core_based_statistical_areas(cb =TRUE, year =2020) %>%filter(str_detect(NAME, "Los Angeles")) %>%st_transform(4267) %>%print()
Simple feature collection with 1 feature and 9 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: -118.9437 ymin: 32.80142 xmax: -117.4124 ymax: 34.82331
Geodetic CRS: NAD27
CSAFP CBSAFP AFFGEOID GEOID NAME
1 348 31080 310M600US31080 31080 Los Angeles-Long Beach-Anaheim, CA
NAMELSAD LSAD ALAND AWATER
1 Los Angeles-Long Beach-Anaheim, CA Metro Area M1 12566940582 2193795620
geometry
1 MULTIPOLYGON (((-118.6035 3...
Plot:
ggplot() +geom_sf(data = ca_tracts, fill ="white", color ="grey") +geom_sf(data = la_metro, fill =NA, color ="red") +theme_void() +labs(title ="Census tracts relative to LA CBSA")
Spatial subsets that intersect:
ca_tracts_intersect <- ca_tracts %>%st_filter(la_metro, .predicate = st_intersects)ggplot() +geom_sf(data = ca_tracts_intersect, fill ="white", color ="grey") +geom_sf(data = la_metro, fill =NA, color ="red") +theme_void() +labs(title ="Census tracts that intersect or border with the Los Angeles CBSA")
Predicate st_within:
ca_tracts_within <- ca_tracts %>%st_filter(la_metro, .predicate = st_within)ggplot() +geom_sf(data = ca_tracts_within, fill ="white", color ="grey") +geom_sf(data = la_metro, fill =NA, color ="red") +theme_void() +labs(title ="Census tracts within the Los Angeles CBSA")
2.1 Spatial joins and group-wise spatial analysis
Total population sizes in the Metro Statistical Areas in Texas:
Simple feature collection with 3189 features and 10 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: 1538292 ymin: 7167200 xmax: 2045975 ymax: 7705975
Projected CRS: NAD83(2011) / Texas Centric Albers Equal Area
First 10 features:
GEOID_tracts NAME_tracts variable_tracts
1 48113019204 Census Tract 192.04, Dallas County, Texas DP05_0071P
3 48029190601 Census Tract 1906.01, Bexar County, Texas DP05_0071P
8 48201311900 Census Tract 3119, Harris County, Texas DP05_0071P
9 48113015500 Census Tract 155, Dallas County, Texas DP05_0071P
11 48439102000 Census Tract 1020, Tarrant County, Texas DP05_0071P
13 48201450200 Census Tract 4502, Harris County, Texas DP05_0071P
14 48201450400 Census Tract 4504, Harris County, Texas DP05_0071P
22 48157670300 Census Tract 6703, Fort Bend County, Texas DP05_0071P
25 48201554502 Census Tract 5545.02, Harris County, Texas DP05_0071P
27 48121020503 Census Tract 205.03, Denton County, Texas DP05_0071P
estimate_tracts moe_tracts GEOID_metro
1 58.1 5.7 19100
3 86.2 6.7 41700
8 84.9 5.8 26420
9 56.6 7.5 19100
11 15.7 6.4 19100
13 10.7 3.9 26420
14 26.8 13.1 26420
22 27.0 5.8 26420
25 13.4 3.0 26420
27 35.3 8.7 19100
NAME_metro variable_metro
1 Dallas-Fort Worth-Arlington, TX Metro Area B01003_001
3 San Antonio-New Braunfels, TX Metro Area B01003_001
8 Houston-The Woodlands-Sugar Land, TX Metro Area B01003_001
9 Dallas-Fort Worth-Arlington, TX Metro Area B01003_001
11 Dallas-Fort Worth-Arlington, TX Metro Area B01003_001
13 Houston-The Woodlands-Sugar Land, TX Metro Area B01003_001
14 Houston-The Woodlands-Sugar Land, TX Metro Area B01003_001
22 Houston-The Woodlands-Sugar Land, TX Metro Area B01003_001
25 Houston-The Woodlands-Sugar Land, TX Metro Area B01003_001
27 Dallas-Fort Worth-Arlington, TX Metro Area B01003_001
estimate_metro moe_metro geometry
1 7573136 NA MULTIPOLYGON (((1801563 765...
3 2550960 NA MULTIPOLYGON (((1642736 726...
8 7066140 NA MULTIPOLYGON (((1950592 729...
9 7573136 NA MULTIPOLYGON (((1778712 763...
11 7573136 NA MULTIPOLYGON (((1746016 762...
13 7066140 NA MULTIPOLYGON (((1925521 730...
14 7066140 NA MULTIPOLYGON (((1922292 730...
22 7066140 NA MULTIPOLYGON (((1935603 728...
25 7066140 NA MULTIPOLYGON (((1918552 732...
27 7573136 NA MULTIPOLYGON (((1766859 768...
Visualize:
hispanic_by_metro %>%mutate(NAME_metro =str_replace(NAME_metro, ", TX Metro Area", "")) %>%ggplot() +geom_density(aes(x = estimate_tracts), color ="navy", fill ="navy", alpha =0.4) +theme_minimal() +facet_wrap(~NAME_metro) +labs(title ="Distribution of Hispanic/Latino population by Census tract",subtitle ="Largest metropolitan areas in Texas",y ="Kernel density estimate",x ="Percent Hispanic/Latino in Census tract")
Simple feature collection with 8 features and 32 fields
Geometry type: POINT
Dimension: XY
Bounding box: xmin: -118.186 ymin: 33.56038 xmax: -117.6645 ymax: 33.80818
Geodetic CRS: NAD27
OBJECTID ID
1 478 0070892868
2 495 0030492691
3 502 0051292668
4 503 0052792705
5 519 0006092691
6 881 0026390806
7 886 0046390801
8 948 0011090806
NAME
1 CHILDREN'S HOSPITAL OF ORANGE COUNTY
2 PROVIDENCE MISSION HOSPITAL
3 UNIVERSITY OF CALIFORNIA IRVINE MEDICAL CENTER
4 ORANGE COUNTY GLOBAL MEDICAL CENTER
5 CHILDREN'S HOSPITAL AT MISSION
6 MEMORIALCARE LONG BEACH MEDICAL CENTER
7 ST. MARY MEDICAL CENTER
8 MEMORIALCARE MILLER CHILDREN'S AND WOMEN'S HOSPITAL LONG BEACH
ADDRESS CITY STATE ZIP ZIP4 TELEPHONE
1 1201 W LA VETA AVE ORANGE CA 92868 4203 (818) 267-7478
2 27700 MEDICAL CENTER RD MISSION VIEJO CA 92691 6426 (949) 364-4840
3 101 THE CITY DR S ORANGE CA 92868 3201 (714) 453-7880
4 1001 N TUSTIN AVE SANTA ANA CA 92705 3502 (714) 953-3610
5 27700 MEDICAL CENTER RD MISSION VIEJO CA 92691 6426 (818) 267-7478
6 2801 ATLANTIC AVE LONG BEACH CA 90806 1701 (562) 933-1902
7 1050 LINDEN AVE LONG BEACH CA 90813 3321 (562) 491-9000
8 2801 ATLANTIC AVE LONG BEACH CA 90806 1701 (562) 933-8002
TYPE STATUS POPULATION COUNTY COUNTYFIPS COUNTRY LATITUDE
1 CHILDREN OPEN 334 ORANGE 06059 USA 33.78081
2 GENERAL ACUTE CARE OPEN 345 ORANGE 06059 USA 33.56102
3 GENERAL ACUTE CARE OPEN 459 ORANGE 06059 USA 33.78879
4 GENERAL ACUTE CARE OPEN 254 ORANGE 06059 USA 33.75438
5 CHILDREN OPEN 54 ORANGE 06059 USA 33.56040
6 GENERAL ACUTE CARE OPEN 411 LOS ANGELES 06037 USA 33.80820
7 GENERAL ACUTE CARE OPEN 360 LOS ANGELES 06037 USA 33.78042
8 CHILDREN OPEN 357 LOS ANGELES 06037 USA 33.80817
LONGITUDE NAICS_CODE NAICS_DESC
1 -117.8658 622110 CHILDREN'S HOSPITALS, GENERAL
2 -117.6654 622110 GENERAL MEDICAL AND SURGICAL HOSPITALS
3 -117.8887 622110 GENERAL MEDICAL AND SURGICAL HOSPITALS
4 -117.8334 622110 GENERAL MEDICAL AND SURGICAL HOSPITALS
5 -117.6658 622110 CHILDREN'S HOSPITALS, GENERAL
6 -118.1869 622110 GENERAL MEDICAL AND SURGICAL HOSPITALS
7 -118.1861 622110 GENERAL MEDICAL AND SURGICAL HOSPITALS
8 -118.1855 622110 CHILDREN'S HOSPITALS, GENERAL
SOURCE
1 https://data.chhs.ca.gov/dataset/3b5b80e8-6b8d-4715-b3c0-2699af6e72e5/resource/098bbc36-044d-441f-9442-1f4db4d8aaa0/download/healthcare_facility_locations.xlsx
2 https://data.chhs.ca.gov/dataset/3b5b80e8-6b8d-4715-b3c0-2699af6e72e5/resource/098bbc36-044d-441f-9442-1f4db4d8aaa0/download/healthcare_facility_locations.xlsx
3 https://data.chhs.ca.gov/dataset/3b5b80e8-6b8d-4715-b3c0-2699af6e72e5/resource/098bbc36-044d-441f-9442-1f4db4d8aaa0/download/healthcare_facility_locations.xlsx
4 https://data.chhs.ca.gov/dataset/3b5b80e8-6b8d-4715-b3c0-2699af6e72e5/resource/098bbc36-044d-441f-9442-1f4db4d8aaa0/download/healthcare_facility_locations.xlsx
5 https://data.chhs.ca.gov/dataset/3b5b80e8-6b8d-4715-b3c0-2699af6e72e5/resource/098bbc36-044d-441f-9442-1f4db4d8aaa0/download/healthcare_facility_locations.xlsx
6 https://data.chhs.ca.gov/dataset/3b5b80e8-6b8d-4715-b3c0-2699af6e72e5/resource/098bbc36-044d-441f-9442-1f4db4d8aaa0/download/healthcare_facility_locations.xlsx
7 https://data.chhs.ca.gov/dataset/3b5b80e8-6b8d-4715-b3c0-2699af6e72e5/resource/098bbc36-044d-441f-9442-1f4db4d8aaa0/download/healthcare_facility_locations.xlsx
8 https://data.chhs.ca.gov/dataset/3b5b80e8-6b8d-4715-b3c0-2699af6e72e5/resource/098bbc36-044d-441f-9442-1f4db4d8aaa0/download/healthcare_facility_locations.xlsx
SOURCEDATE VAL_METHOD VAL_DATE WEBSITE STATE_ID
1 1.633046e+12 IMAGERY/OTHER 1.421107e+12 NOT AVAILABLE 060000007
2 1.633046e+12 IMAGERY/OTHER 1.646006e+12 NOT AVAILABLE 060000060
3 1.633046e+12 IMAGERY/OTHER 1.391990e+12 NOT AVAILABLE 060000071
4 1.633046e+12 IMAGERY/OTHER 1.391990e+12 NOT AVAILABLE 060000073
5 1.633046e+12 IMAGERY/OTHER 1.394582e+12 NOT AVAILABLE 060001207
6 1.633046e+12 IMAGERY/OTHER 1.391990e+12 NOT AVAILABLE 930000095
7 1.633046e+12 IMAGERY 1.391990e+12 NOT AVAILABLE 930000103
8 1.633046e+12 IMAGERY/OTHER 1.394582e+12 NOT AVAILABLE 930001709
ALT_NAME ST_FIPS OWNER
1 CHILDREN'S HOSPITAL OF ORANGE COUNTY 06 NON-PROFIT
2 MISSION HOSPITAL REGIONAL MEDICAL CENTER 06 NON-PROFIT
3 UNIVERSITY OF CALIFORNIA BOARD OF REGENTS 06 GOVERNMENT - STATE
4 ORANGE COUNTY GLOBAL MEDICAL CENTER, INC. 06 PROPRIETARY
5 CHILDREN'S HOSPITAL AT MISSION 06 NON-PROFIT
6 LONG BEACH MEMORIAL MEDICAL CENTER 06 NON-PROFIT
7 DIGNITY HEALTH 06 NON-PROFIT
8 LONG BEACH MEMORIAL MEDICAL CENTER 06 NON-PROFIT
TTL_STAFF BEDS TRAUMA HELIPAD
1 -999 334 LEVEL II PEDIATRIC Y
2 -999 345 LEVEL II ADULT, LEVEL II PEDIATRIC Y
3 -999 459 LEVEL I ADULT, LEVEL II PEDIATRIC Y
4 -999 254 LEVEL II Y
5 -999 54 LEVEL II PEDIATRIC Y
6 -999 411 LEVEL II ADULT, LEVEL II PEDIATRIC Y
7 -999 360 LEVEL II Y
8 -999 357 LEVEL II ADULT, LEVEL II PEDIATRIC Y
geometry
1 POINT (-117.8649 33.78079)
2 POINT (-117.6645 33.56099)
3 POINT (-117.8878 33.78877)
4 POINT (-117.8325 33.75437)
5 POINT (-117.665 33.56038)
6 POINT (-118.186 33.80818)
7 POINT (-118.1852 33.78041)
8 POINT (-118.1846 33.80816)
ggplot() +geom_sf(data = oc_subdivs, color ="NA", fill ="grey50") +geom_sf(data = oc_trauma, color ="red") +theme_void()
min_time <-apply(times, 1, min)oc_subdivs$time <- min_timeggplot(oc_subdivs, aes(fill = time)) +geom_sf(color =NA) +scale_fill_viridis_c(option ="magma") +theme_void() +labs(fill ="Time (minutes)",title ="Travel time to nearest Level I trauma hospital",subtitle ="Census tracts in Orange County, CA",caption ="Data sources: US Census Bureau, US DHS, Mapbox")
3.3 Catchment areas: buffers and isochrones
ucla_hosp <-filter(trauma, ID =="0038190095")# 5 km bufferbuf5km <-st_buffer(ucla_hosp, dist =5000) # 10 min isochrone given current trafficiso10min <-mb_isochrone( ucla_hosp, time =10, profile ="driving-traffic",# depart_at = "2023-07-05T17:00" )
Mapping:
library(leaflet)library(leafsync)hospital_icon <-makeAwesomeIcon(icon ="ios-medical", markerColor ="red",library ="ion")# The Leaflet package requires data be in CRS 4326map1 <-leaflet() %>%addTiles() %>%addPolygons(data =st_transform(buf5km, 4326)) %>%addAwesomeMarkers(data =st_transform(ucla_hosp, 4326),icon = hospital_icon)map2 <-leaflet() %>%addTiles() %>%addPolygons(data = iso10min) %>%addAwesomeMarkers(data =st_transform(ucla_hosp, 4326),icon = hospital_icon)sync(map1, map2)
4 Spatial neighborhoods and spatial weights matrices
Simple feature collection with 3088 features and 6 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: -118.9437 ymin: 32.80142 xmax: -117.4124 ymax: 34.82331
Geodetic CRS: NAD27
First 10 features:
GEOID NAME variable
1 06037300100 Census Tract 3001, Los Angeles County, California B01002_001
2 06037620601 Census Tract 6206.01, Los Angeles County, California B01002_001
3 06037291210 Census Tract 2912.10, Los Angeles County, California B01002_001
4 06037573902 Census Tract 5739.02, Los Angeles County, California B01002_001
5 06037571502 Census Tract 5715.02, Los Angeles County, California B01002_001
6 06037570003 Census Tract 5700.03, Los Angeles County, California B01002_001
7 06037603301 Census Tract 6033.01, Los Angeles County, California B01002_001
8 06037603500 Census Tract 6035, Los Angeles County, California B01002_001
9 06037554516 Census Tract 5545.16, Los Angeles County, California B01002_001
10 06037554517 Census Tract 5545.17, Los Angeles County, California B01002_001
estimate moe geometry lag_estimate
1 44.5 3.9 MULTIPOLYGON (((-118.2477 3... 45.15000
2 38.7 3.3 MULTIPOLYGON (((-118.3718 3... 39.00000
3 37.9 3.3 MULTIPOLYGON (((-118.2909 3... 39.48571
4 51.4 3.2 MULTIPOLYGON (((-118.0807 3... 41.05000
5 42.4 3.6 MULTIPOLYGON (((-118.1918 3... 35.37778
6 39.6 3.1 MULTIPOLYGON (((-118.1458 3... 35.64286
7 45.5 5.0 MULTIPOLYGON (((-118.3126 3... 44.06667
8 40.2 2.1 MULTIPOLYGON (((-118.3256 3... 38.05000
9 47.2 5.4 MULTIPOLYGON (((-118.0714 3... 43.44444
10 39.1 3.7 MULTIPOLYGON (((-118.0628 3... 46.78333
ggplot(la_tracts, aes(x = estimate, y = lag_estimate)) +geom_point(alpha =0.3) +geom_abline(color ="red") +theme_minimal() +labs(title ="Median age by Census tract, Los Angeles CA",x ="Median age",y ="Spatial lag, median age", caption ="Data source: 2016-2020 ACS.\nSpatial relationships based on queens-case polygon contiguity.")
Moran’s I test:
moran.test(la_tracts$estimate, weights)
Moran I test under randomisation
data: la_tracts$estimate
weights: weights
Moran I statistic standard deviate = 46.001, p-value < 2.2e-16
alternative hypothesis: greater
sample estimates:
Moran I statistic Expectation Variance
0.4723661752 -0.0003239391 0.0001055896
5.1 Local spatial autocorrelation
# For Gi*, re-compute the weights with `include.self()`localg_weights <-nb2listw(include.self(neighbors))la_tracts$localG <-localG(la_tracts$estimate, localg_weights)ggplot(la_tracts) +geom_sf(aes(fill = localG), color =NA) +scale_fill_distiller(palette ="RdYlBu") +theme_void() +labs(fill ="Local Gi* statistic")
